Overview

Dataset statistics

Number of variables17
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory138.2 B

Variable types

Text1
Numeric16

Alerts

AT is highly overall correlated with BE and 14 other fieldsHigh correlation
BE is highly overall correlated with AT and 14 other fieldsHigh correlation
DE is highly overall correlated with AT and 14 other fieldsHigh correlation
DK is highly overall correlated with AT and 14 other fieldsHigh correlation
ES is highly overall correlated with AT and 14 other fieldsHigh correlation
FI is highly overall correlated with AT and 14 other fieldsHigh correlation
FR is highly overall correlated with AT and 14 other fieldsHigh correlation
GB is highly overall correlated with AT and 14 other fieldsHigh correlation
IE is highly overall correlated with AT and 14 other fieldsHigh correlation
IT is highly overall correlated with AT and 14 other fieldsHigh correlation
NL is highly overall correlated with AT and 14 other fieldsHigh correlation
NO is highly overall correlated with AT and 14 other fieldsHigh correlation
PL is highly overall correlated with AT and 14 other fieldsHigh correlation
PT is highly overall correlated with AT and 14 other fieldsHigh correlation
SE is highly overall correlated with AT and 14 other fieldsHigh correlation
Total general is highly overall correlated with AT and 14 other fieldsHigh correlation
Fecha has unique valuesUnique
DE has unique valuesUnique
DK has unique valuesUnique
ES has unique valuesUnique
FI has unique valuesUnique
FR has unique valuesUnique
GB has unique valuesUnique
IE has unique valuesUnique
NO has unique valuesUnique
SE has unique valuesUnique
IT has unique valuesUnique
PL has unique valuesUnique
NL has unique valuesUnique
BE has unique valuesUnique
PT has unique valuesUnique
AT has unique valuesUnique
Total general has unique valuesUnique

Reproduction

Analysis started2024-02-11 16:34:37.771951
Analysis finished2024-02-11 16:35:22.293113
Duration44.52 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Fecha
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-02-11T17:35:22.710763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.0983607
Min length7

Characters and Unicode

Total characters433
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row2019-01
2nd row2019-02
3rd row2019-03
4th row2019-04
5th row2019-05
ValueCountFrequency (%)
2019-01 1
 
1.6%
2020-04 1
 
1.6%
2019-03 1
 
1.6%
2019-04 1
 
1.6%
2019-05 1
 
1.6%
2019-06 1
 
1.6%
2019-07 1
 
1.6%
2019-08 1
 
1.6%
2019-09 1
 
1.6%
2019-10 1
 
1.6%
Other values (52) 52
83.9%
2024-02-11T17:35:23.502187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 130
30.0%
0 122
28.2%
- 60
13.9%
1 49
 
11.3%
9 17
 
3.9%
3 17
 
3.9%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (11) 18
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.1%
Dash Punctuation 60
 
13.9%
Lowercase Letter 11
 
2.5%
Uppercase Letter 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 130
36.1%
0 122
33.9%
1 49
 
13.6%
9 17
 
4.7%
3 17
 
4.7%
5 5
 
1.4%
6 5
 
1.4%
7 5
 
1.4%
4 5
 
1.4%
8 5
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
18.2%
l 2
18.2%
e 2
18.2%
o 1
9.1%
t 1
9.1%
g 1
9.1%
n 1
9.1%
r 1
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 421
97.2%
Latin 12
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 130
30.9%
0 122
29.0%
- 60
14.3%
1 49
 
11.6%
9 17
 
4.0%
3 17
 
4.0%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (2) 6
 
1.4%
Latin
ValueCountFrequency (%)
a 2
16.7%
l 2
16.7%
e 2
16.7%
T 1
8.3%
o 1
8.3%
t 1
8.3%
g 1
8.3%
n 1
8.3%
r 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 130
30.0%
0 122
28.2%
- 60
13.9%
1 49
 
11.3%
9 17
 
3.9%
3 17
 
3.9%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (11) 18
 
4.2%

DE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1343633.7
Minimum145490
Maximum40980827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:23.743970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum145490
5-th percentile299951
Q1422529
median712193
Q3901101
95-th percentile1095376
Maximum40980827
Range40835337
Interquartile range (IQR)478572

Descriptive statistics

Standard deviation5166080.5
Coefficient of variation (CV)3.8448579
Kurtosis60.679289
Mean1343633.7
Median Absolute Deviation (MAD)218702
Skewness7.7799154
Sum81961654
Variance2.6688388 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:24.040016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
816231 1
 
1.6%
786111 1
 
1.6%
1033650 1
 
1.6%
750302 1
 
1.6%
712193 1
 
1.6%
950761 1
 
1.6%
1054705 1
 
1.6%
1026430 1
 
1.6%
936376 1
 
1.6%
995553 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
145490 1
1.6%
234032 1
1.6%
259217 1
1.6%
299951 1
1.6%
321133 1
1.6%
323336 1
1.6%
326744 1
1.6%
351966 1
1.6%
359428 1
1.6%
388563 1
1.6%
ValueCountFrequency (%)
40980827 1
1.6%
1179389 1
1.6%
1156334 1
1.6%
1095376 1
1.6%
1054705 1
1.6%
1033650 1
1.6%
1026430 1
1.6%
1019397 1
1.6%
995553 1
1.6%
977756 1
1.6%

DK
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean536294.82
Minimum27663
Maximum16356992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:24.344271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27663
5-th percentile36592
Q1161350
median281733
Q3410755
95-th percentile503423
Maximum16356992
Range16329329
Interquartile range (IQR)249405

Descriptive statistics

Standard deviation2064988.7
Coefficient of variation (CV)3.850473
Kurtosis60.30813
Mean536294.82
Median Absolute Deviation (MAD)129022
Skewness7.7447222
Sum32713984
Variance4.2641785 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:24.678100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
469044 1
 
1.6%
268513 1
 
1.6%
303478 1
 
1.6%
288310 1
 
1.6%
276436 1
 
1.6%
446413 1
 
1.6%
357094 1
 
1.6%
387070 1
 
1.6%
433070 1
 
1.6%
481723 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
27663 1
1.6%
34283 1
1.6%
35084 1
1.6%
36592 1
1.6%
38648 1
1.6%
40168 1
1.6%
40669 1
1.6%
45449 1
1.6%
48227 1
1.6%
53386 1
1.6%
ValueCountFrequency (%)
16356992 1
1.6%
534469 1
1.6%
509747 1
1.6%
503423 1
1.6%
489120 1
1.6%
481723 1
1.6%
478102 1
1.6%
469629 1
1.6%
469044 1
1.6%
465141 1
1.6%

ES
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1386994.4
Minimum57992
Maximum42303329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:25.000684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57992
5-th percentile127775
Q1282070
median491574
Q31131294
95-th percentile1778194
Maximum42303329
Range42245337
Interquartile range (IQR)849224

Descriptive statistics

Standard deviation5350924.6
Coefficient of variation (CV)3.8579281
Kurtosis59.819226
Mean1386994.4
Median Absolute Deviation (MAD)352861
Skewness7.6990351
Sum84606658
Variance2.8632394 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:25.340276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
359708 1
 
1.6%
695290 1
 
1.6%
996783 1
 
1.6%
1038695 1
 
1.6%
811998 1
 
1.6%
1283805 1
 
1.6%
1478936 1
 
1.6%
1778194 1
 
1.6%
1870392 1
 
1.6%
2034456 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
57992 1
1.6%
105587 1
1.6%
115356 1
1.6%
127775 1
1.6%
130333 1
1.6%
138713 1
1.6%
151581 1
1.6%
167937 1
1.6%
169701 1
1.6%
170220 1
1.6%
ValueCountFrequency (%)
42303329 1
1.6%
2034456 1
1.6%
1870392 1
1.6%
1778194 1
1.6%
1599633 1
1.6%
1478936 1
1.6%
1455114 1
1.6%
1341695 1
1.6%
1317979 1
1.6%
1283805 1
1.6%

FI
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean183915.51
Minimum13859
Maximum5609423
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:25.572604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13859
5-th percentile14980
Q133879
median99662
Q3138173
95-th percentile185292
Maximum5609423
Range5595564
Interquartile range (IQR)104294

Descriptive statistics

Standard deviation708488.12
Coefficient of variation (CV)3.8522478
Kurtosis60.191325
Mean183915.51
Median Absolute Deviation (MAD)53992
Skewness7.7337462
Sum11218846
Variance5.0195541 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:25.812281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
155539 1
 
1.6%
55973 1
 
1.6%
114034 1
 
1.6%
105925 1
 
1.6%
80758 1
 
1.6%
109367 1
 
1.6%
129773 1
 
1.6%
137616 1
 
1.6%
126880 1
 
1.6%
153654 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
13859 1
1.6%
13880 1
1.6%
14308 1
1.6%
14980 1
1.6%
15893 1
1.6%
16326 1
1.6%
16518 1
1.6%
17490 1
1.6%
19519 1
1.6%
20532 1
1.6%
ValueCountFrequency (%)
5609423 1
1.6%
186717 1
1.6%
185906 1
1.6%
185292 1
1.6%
184705 1
1.6%
184364 1
1.6%
183705 1
1.6%
181836 1
1.6%
158298 1
1.6%
157903 1
1.6%

FR
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean721226.85
Minimum33644
Maximum21997419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:26.250285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33644
5-th percentile78519
Q1186230
median395652
Q3522086
95-th percentile782600
Maximum21997419
Range21963775
Interquartile range (IQR)335856

Descriptive statistics

Standard deviation2777495.6
Coefficient of variation (CV)3.8510707
Kurtosis60.268711
Mean721226.85
Median Absolute Deviation (MAD)152772
Skewness7.741149
Sum43994838
Variance7.7144819 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:26.485494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448329 1
 
1.6%
490515 1
 
1.6%
528222 1
 
1.6%
454516 1
 
1.6%
322502 1
 
1.6%
474834 1
 
1.6%
682976 1
 
1.6%
788488 1
 
1.6%
782600 1
 
1.6%
869623 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
33644 1
1.6%
36523 1
1.6%
55252 1
1.6%
78519 1
1.6%
79233 1
1.6%
88569 1
1.6%
95551 1
1.6%
97023 1
1.6%
101648 1
1.6%
102359 1
1.6%
ValueCountFrequency (%)
21997419 1
1.6%
869623 1
1.6%
788488 1
1.6%
782600 1
1.6%
696668 1
1.6%
682976 1
1.6%
652463 1
1.6%
623060 1
1.6%
612532 1
1.6%
594010 1
1.6%

GB
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4738752.8
Minimum439866
Maximum1.4453196 Ɨ 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:26.812675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439866
5-th percentile616876
Q11109960
median2430888
Q33448650
95-th percentile4405741
Maximum1.4453196 Ɨ 108
Range1.4409209 Ɨ 108
Interquartile range (IQR)2338690

Descriptive statistics

Standard deviation18241949
Coefficient of variation (CV)3.8495253
Kurtosis60.370531
Mean4738752.8
Median Absolute Deviation (MAD)1206101
Skewness7.7507454
Sum2.8906392 Ɨ 108
Variance3.3276869 Ɨ 1014
MonotonicityNot monotonic
2024-02-11T17:35:27.116057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3681023 1
 
1.6%
2391429 1
 
1.6%
2293464 1
 
1.6%
1834373 1
 
1.6%
1322039 1
 
1.6%
2876480 1
 
1.6%
3053419 1
 
1.6%
3428961 1
 
1.6%
3534303 1
 
1.6%
4990564 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
439866 1
1.6%
500377 1
1.6%
611253 1
1.6%
616876 1
1.6%
678202 1
1.6%
714116 1
1.6%
743713 1
1.6%
852579 1
1.6%
881733 1
1.6%
911554 1
1.6%
ValueCountFrequency (%)
144531960 1
1.6%
4990564 1
1.6%
4975132 1
1.6%
4405741 1
1.6%
4367503 1
1.6%
4266707 1
1.6%
4035708 1
1.6%
3983659 1
1.6%
3969761 1
1.6%
3909521 1
1.6%

IE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean271619.41
Minimum23367
Maximum8284392
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:27.366438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23367
5-th percentile29537
Q171433
median151578
Q3206401
95-th percentile234601
Maximum8284392
Range8261025
Interquartile range (IQR)134968

Descriptive statistics

Standard deviation1045528.5
Coefficient of variation (CV)3.8492408
Kurtosis60.389359
Mean271619.41
Median Absolute Deviation (MAD)61176
Skewness7.7523971
Sum16568784
Variance1.0931299 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:27.665968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
213282 1
 
1.6%
123999 1
 
1.6%
129436 1
 
1.6%
118807 1
 
1.6%
107198 1
 
1.6%
199573 1
 
1.6%
208282 1
 
1.6%
234186 1
 
1.6%
221644 1
 
1.6%
234882 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
23367 1
1.6%
25539 1
1.6%
27648 1
1.6%
29537 1
1.6%
30277 1
1.6%
33064 1
1.6%
34031 1
1.6%
34317 1
1.6%
34748 1
1.6%
36455 1
1.6%
ValueCountFrequency (%)
8284392 1
1.6%
253413 1
1.6%
234882 1
1.6%
234601 1
1.6%
234186 1
1.6%
231233 1
1.6%
230321 1
1.6%
225832 1
1.6%
224500 1
1.6%
221644 1
1.6%

NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296822.07
Minimum20609
Maximum9053073
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:28.038464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20609
5-th percentile22677
Q173372
median147297
Q3217513
95-th percentile319890
Maximum9053073
Range9032464
Interquartile range (IQR)144141

Descriptive statistics

Standard deviation1143525.1
Coefficient of variation (CV)3.8525609
Kurtosis60.170713
Mean296822.07
Median Absolute Deviation (MAD)73925
Skewness7.7319218
Sum18106146
Variance1.3076496 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:28.440632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
225411 1
 
1.6%
114116 1
 
1.6%
155964 1
 
1.6%
166351 1
 
1.6%
147297 1
 
1.6%
209085 1
 
1.6%
224507 1
 
1.6%
252627 1
 
1.6%
299802 1
 
1.6%
383244 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
20609 1
1.6%
22460 1
1.6%
22658 1
1.6%
22677 1
1.6%
22931 1
1.6%
25009 1
1.6%
26279 1
1.6%
26536 1
1.6%
27200 1
1.6%
29404 1
1.6%
ValueCountFrequency (%)
9053073 1
1.6%
383244 1
1.6%
327411 1
1.6%
319890 1
1.6%
299802 1
1.6%
297530 1
1.6%
285950 1
1.6%
278807 1
1.6%
268052 1
1.6%
258738 1
1.6%

SE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean875232.13
Minimum42012
Maximum26694580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:28.768227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42012
5-th percentile76333
Q1231637
median473875
Q3653206
95-th percentile862882
Maximum26694580
Range26652568
Interquartile range (IQR)421569

Descriptive statistics

Standard deviation3370587.6
Coefficient of variation (CV)3.8510784
Kurtosis60.268246
Mean875232.13
Median Absolute Deviation (MAD)185273
Skewness7.7410012
Sum53389160
Variance1.1360861 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:29.025745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
520131 1
 
1.6%
306442 1
 
1.6%
355345 1
 
1.6%
300693 1
 
1.6%
231637 1
 
1.6%
408362 1
 
1.6%
461860 1
 
1.6%
473875 1
 
1.6%
658009 1
 
1.6%
789847 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
42012 1
1.6%
51513 1
1.6%
73570 1
1.6%
76333 1
1.6%
80389 1
1.6%
81699 1
1.6%
84106 1
1.6%
94938 1
1.6%
101163 1
1.6%
102404 1
1.6%
ValueCountFrequency (%)
26694580 1
1.6%
941619 1
1.6%
905972 1
1.6%
862882 1
1.6%
858753 1
1.6%
810975 1
1.6%
789847 1
1.6%
751022 1
1.6%
749564 1
1.6%
742730 1
1.6%

IT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean934882.79
Minimum30335
Maximum28513925
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:29.348234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30335
5-th percentile81200
Q1190271
median461054
Q3706786
95-th percentile1030108
Maximum28513925
Range28483590
Interquartile range (IQR)516515

Descriptive statistics

Standard deviation3602832.1
Coefficient of variation (CV)3.8537795
Kurtosis60.090689
Mean934882.79
Median Absolute Deviation (MAD)267409
Skewness7.7244761
Sum57027850
Variance1.2980399 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:29.635315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
535228 1
 
1.6%
372029 1
 
1.6%
611646 1
 
1.6%
570418 1
 
1.6%
471364 1
 
1.6%
593174 1
 
1.6%
885934 1
 
1.6%
1030108 1
 
1.6%
1191971 1
 
1.6%
1278660 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
30335 1
1.6%
50972 1
1.6%
76710 1
1.6%
81200 1
1.6%
82446 1
1.6%
86519 1
1.6%
89939 1
1.6%
94089 1
1.6%
96231 1
1.6%
96279 1
1.6%
ValueCountFrequency (%)
28513925 1
1.6%
1278660 1
1.6%
1191971 1
1.6%
1030108 1
1.6%
983062 1
1.6%
971461 1
1.6%
890879 1
1.6%
885934 1
1.6%
802225 1
1.6%
797832 1
1.6%

PL
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277965.8
Minimum8425
Maximum8477957
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:29.916384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8425
5-th percentile27684
Q171896
median102042
Q3234504
95-th percentile357939
Maximum8477957
Range8469532
Interquartile range (IQR)162608

Descriptive statistics

Standard deviation1072334.5
Coefficient of variation (CV)3.857793
Kurtosis59.827976
Mean277965.8
Median Absolute Deviation (MAD)69420
Skewness7.699995
Sum16955914
Variance1.1499014 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:30.150975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
181442 1
 
1.6%
94098 1
 
1.6%
116028 1
 
1.6%
109407 1
 
1.6%
95657 1
 
1.6%
127001 1
 
1.6%
129422 1
 
1.6%
176285 1
 
1.6%
234504 1
 
1.6%
297214 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
8425 1
1.6%
11084 1
1.6%
26724 1
1.6%
27684 1
1.6%
28103 1
1.6%
29387 1
1.6%
32249 1
1.6%
32528 1
1.6%
32622 1
1.6%
36447 1
1.6%
ValueCountFrequency (%)
8477957 1
1.6%
391473 1
1.6%
381395 1
1.6%
357939 1
1.6%
332436 1
1.6%
299033 1
1.6%
297214 1
1.6%
295543 1
1.6%
291981 1
1.6%
283350 1
1.6%

NL
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300675.9
Minimum14742
Maximum9170615
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:30.367748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14742
5-th percentile40837
Q1100597
median162635
Q3196334
95-th percentile286673
Maximum9170615
Range9155873
Interquartile range (IQR)95737

Descriptive statistics

Standard deviation1156857.9
Coefficient of variation (CV)3.8475247
Kurtosis60.502659
Mean300675.9
Median Absolute Deviation (MAD)43477
Skewness7.763218
Sum18341230
Variance1.3383203 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:30.629026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165829 1
 
1.6%
130070 1
 
1.6%
133337 1
 
1.6%
137127 1
 
1.6%
126814 1
 
1.6%
168021 1
 
1.6%
182190 1
 
1.6%
218240 1
 
1.6%
205174 1
 
1.6%
195751 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
14742 1
1.6%
21629 1
1.6%
40787 1
1.6%
40837 1
1.6%
42862 1
1.6%
44494 1
1.6%
45879 1
1.6%
53140 1
1.6%
61972 1
1.6%
63894 1
1.6%
ValueCountFrequency (%)
9170615 1
1.6%
313813 1
1.6%
287296 1
1.6%
286673 1
1.6%
265390 1
1.6%
264781 1
1.6%
252639 1
1.6%
247345 1
1.6%
247189 1
1.6%
235825 1
1.6%

BE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean234592.33
Minimum26844
Maximum7155066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:30.964984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26844
5-th percentile36151
Q178618
median137047
Q3159556
95-th percentile177653
Maximum7155066
Range7128222
Interquartile range (IQR)80938

Descriptive statistics

Standard deviation902168.56
Coefficient of variation (CV)3.8456866
Kurtosis60.624381
Mean234592.33
Median Absolute Deviation (MAD)31433
Skewness7.7746373
Sum14310132
Variance8.1390812 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:31.283742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127326 1
 
1.6%
139048 1
 
1.6%
153828 1
 
1.6%
130092 1
 
1.6%
113601 1
 
1.6%
138603 1
 
1.6%
148545 1
 
1.6%
157200 1
 
1.6%
168869 1
 
1.6%
173502 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
26844 1
1.6%
30719 1
1.6%
34696 1
1.6%
36151 1
1.6%
36229 1
1.6%
37135 1
1.6%
37491 1
1.6%
37806 1
1.6%
38219 1
1.6%
52599 1
1.6%
ValueCountFrequency (%)
7155066 1
1.6%
204674 1
1.6%
189881 1
1.6%
177653 1
1.6%
173502 1
1.6%
172151 1
1.6%
171378 1
1.6%
169281 1
1.6%
168869 1
1.6%
166750 1
1.6%

PT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean221842.36
Minimum9880
Maximum6766192
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:31.568459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9880
5-th percentile16856
Q161279
median117546
Q3182317
95-th percentile222847
Maximum6766192
Range6756312
Interquartile range (IQR)121038

Descriptive statistics

Standard deviation854642.2
Coefficient of variation (CV)3.8524752
Kurtosis60.176363
Mean221842.36
Median Absolute Deviation (MAD)59581
Skewness7.7323604
Sum13532384
Variance7.3041329 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:31.921251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61279 1
 
1.6%
161123 1
 
1.6%
158226 1
 
1.6%
163504 1
 
1.6%
146644 1
 
1.6%
200225 1
 
1.6%
186639 1
 
1.6%
195903 1
 
1.6%
203676 1
 
1.6%
223321 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
9880 1
1.6%
10446 1
1.6%
16407 1
1.6%
16856 1
1.6%
18738 1
1.6%
20737 1
1.6%
24004 1
1.6%
25195 1
1.6%
25559 1
1.6%
26109 1
1.6%
ValueCountFrequency (%)
6766192 1
1.6%
234636 1
1.6%
223321 1
1.6%
222847 1
1.6%
214956 1
1.6%
211489 1
1.6%
210705 1
1.6%
209990 1
1.6%
203676 1
1.6%
200225 1
1.6%

AT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111878.03
Minimum7597
Maximum3412280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:32.260997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7597
5-th percentile11630
Q131032
median51392
Q391109
95-th percentile103236
Maximum3412280
Range3404683
Interquartile range (IQR)60077

Descriptive statistics

Standard deviation430854.97
Coefficient of variation (CV)3.8511132
Kurtosis60.265928
Mean111878.03
Median Absolute Deviation (MAD)33434
Skewness7.7408047
Sum6824560
Variance1.8563601 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:32.627652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51392 1
 
1.6%
59650 1
 
1.6%
83313 1
 
1.6%
82436 1
 
1.6%
89831 1
 
1.6%
100642 1
 
1.6%
100950 1
 
1.6%
108126 1
 
1.6%
95945 1
 
1.6%
101936 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
7597 1
1.6%
9362 1
1.6%
9901 1
1.6%
11630 1
1.6%
12082 1
1.6%
13007 1
1.6%
13893 1
1.6%
14798 1
1.6%
16224 1
1.6%
17646 1
1.6%
ValueCountFrequency (%)
3412280 1
1.6%
108126 1
1.6%
104215 1
1.6%
103236 1
1.6%
101936 1
1.6%
100950 1
1.6%
100642 1
1.6%
99240 1
1.6%
95945 1
1.6%
95386 1
1.6%

Total general
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12436329
Minimum1524935
Maximum3.7930803 Ɨ 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:33.007854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1524935
5-th percentile1625666
Q14295250
median6936894
Q38307413
95-th percentile11492687
Maximum3.7930803 Ɨ 108
Range3.777831 Ɨ 108
Interquartile range (IQR)4012163

Descriptive statistics

Standard deviation47855271
Coefficient of variation (CV)3.8480223
Kurtosis60.469773
Mean12436329
Median Absolute Deviation (MAD)1984414
Skewness7.7600904
Sum7.5861606 Ɨ 108
Variance2.2901269 Ɨ 1015
MonotonicityNot monotonic
2024-02-11T17:35:33.384627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8011194 1
 
1.6%
6188406 1
 
1.6%
7166754 1
 
1.6%
6250956 1
 
1.6%
5055969 1
 
1.6%
8286346 1
 
1.6%
9285232 1
 
1.6%
10393309 1
 
1.6%
10963215 1
 
1.6%
13203930 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
1524935 1
1.6%
1539930 1
1.6%
1546952 1
1.6%
1625666 1
1.6%
1708520 1
1.6%
1769193 1
1.6%
1839432 1
1.6%
1849632 1
1.6%
1959965 1
1.6%
2004588 1
1.6%
ValueCountFrequency (%)
379308030 1
1.6%
13203930 1
1.6%
11519763 1
1.6%
11492687 1
1.6%
11124911 1
1.6%
10963215 1
1.6%
10467590 1
1.6%
10393309 1
1.6%
10150279 1
1.6%
9767669 1
1.6%

Interactions

2024-02-11T17:35:18.560635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:38.544340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.015881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.474016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.807082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:48.303110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.491367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.684359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:55.099137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:57.676341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:00.819978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:03.585898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.865529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:08.344701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:11.496611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:15.006592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:18.774576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:38.854672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.156297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.611640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.006016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:48.617936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.657087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.811697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:55.268952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:57.845039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.031865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:03.735824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.000724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:08.553105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:11.703448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:15.285966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.003508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:38.977363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.272549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.743360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.178959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:48.733545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.828827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.996485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:55.462939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.016000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.236035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:03.903497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.201385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:08.749770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:11.940831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:15.611224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.178728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.083236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.406897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.874872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.293455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:48.853940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.977271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:53.126800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:55.612309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.181673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.422142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.012806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.344800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:08.962356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:12.115167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:15.812598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.394926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.200032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.531866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:44.025914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.417377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:48.992985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.087929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:53.270541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:55.764443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.343176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.635235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.193880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.485490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:09.155832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:12.294860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.017611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.573188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.328076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.677449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:44.176687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.665740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.115098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.218328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:53.391325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:55.913275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.490450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.813012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.319093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.631978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:09.347858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:12.661177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.268846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.775695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.513296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.833030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:44.342398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.841226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.268404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.337401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:53.531661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.093458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.631873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.987648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.470663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.800706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:09.540629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:12.813423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.513181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.979081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.700527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:41.953527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:44.487661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:46.989697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.398519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.491951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:53.742372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.250811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.793659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.106219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.577935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:06.951463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:09.735107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:12.993329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.727976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.149729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.834440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:42.111732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:44.632493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.103754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.497031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.643044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:53.891951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.402307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.944426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.270767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.704497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.101688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:09.920546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:13.200955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.907523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.343926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:39.995742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:42.281754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:44.764201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.246616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.595149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.758357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.048285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.529893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:59.128213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.414375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.836691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.257438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.107125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:13.470604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:17.123276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.493061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:40.177490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:42.457498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.062158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.518829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.691723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.866945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.190903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.682885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:59.342831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.566924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.996581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.400330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.294383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:13.670630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:17.348234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.640069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:40.302764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:42.622190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.202847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.624212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.787051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:51.976298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.325045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.830308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:59.795145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.731761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.106713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.552067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.460608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:13.894682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:17.546705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.809551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:40.452036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:42.815614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.334570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.720725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:49.873876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.074509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.456948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:57.003031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:59.978797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.896342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.210645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.695797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.633083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:14.085172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:17.752084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.974806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:40.593440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.022995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.444121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.829976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.022800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.214467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.618283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:57.161772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:00.190685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:03.073367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.349725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.855552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.836916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:14.300504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:17.922224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:21.186867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:40.748806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.181828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.557791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:47.980932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.174265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.380724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.771055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:57.337304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:00.375903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:03.238035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.523372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:08.002093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:11.071195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:14.511809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:18.141525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:21.391801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:40.900105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:43.342224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:45.678761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:48.138012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:50.346491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:52.544368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:54.933146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:57.507285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:00.582289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:03.391895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.685073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:08.161196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:11.272231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:14.748462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:18.354363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-02-11T17:35:33.690590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ATBEDEDKESFIFRGBIEITNLNOPLPTSETotal general
AT1.0000.6680.8520.8700.9480.8440.8980.5840.6620.9210.8020.8790.8950.8980.7610.840
BE0.6681.0000.7330.6670.6850.7030.7790.8390.7930.7730.8380.7530.7450.7640.7090.864
DE0.8520.7331.0000.8310.8300.8170.9250.6690.7190.8560.7250.8180.8060.8160.6540.860
DK0.8700.6670.8311.0000.8630.9280.8690.7310.8060.8860.7570.9360.8900.7720.8510.899
ES0.9480.6850.8300.8631.0000.8320.9370.5880.6650.9360.7900.8650.8760.9160.7690.849
FI0.8440.7030.8170.9280.8321.0000.8490.7600.8100.8910.7980.9140.8970.7430.8550.905
FR0.8980.7790.9250.8690.9370.8491.0000.6870.7300.9340.8000.8680.8720.9120.7430.899
GB0.5840.8390.6690.7310.5880.7600.6871.0000.9410.6990.6800.7640.6510.5690.6840.889
IE0.6620.7930.7190.8060.6650.8100.7300.9411.0000.7670.7170.8190.6870.6130.7160.898
IT0.9210.7730.8560.8860.9360.8910.9340.6990.7671.0000.8810.9390.9300.9070.8390.922
NL0.8020.8380.7250.7570.7900.7980.8000.6800.7170.8811.0000.8260.8920.8450.8300.849
NO0.8790.7530.8180.9360.8650.9140.8680.7640.8190.9390.8261.0000.9130.8270.8820.930
PL0.8950.7450.8060.8900.8760.8970.8720.6510.6870.9300.8920.9131.0000.8750.9070.881
PT0.8980.7640.8160.7720.9160.7430.9120.5690.6130.9070.8450.8270.8751.0000.7440.808
SE0.7610.7090.6540.8510.7690.8550.7430.6840.7160.8390.8300.8820.9070.7441.0000.834
Total general0.8400.8640.8600.8990.8490.9050.8990.8890.8980.9220.8490.9300.8810.8080.8341.000

Missing values

2024-02-11T17:35:21.650202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-11T17:35:22.086252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

FechaDEDKESFIFRGBIENOSEITPLNLBEPTATTotal general
02019-01816231469044359708155539448329368102321328222541152013153522818144216582912732661279513928011194
12019-027270904651413565891381733172183025253200931185217542362364964114468896517861862180463716714226
22019-0377361547810239955114986939656531509552212141965725862964600809276312525310315787235479337269160
32019-0468483833380639177310192235101132938882303211445614400094610548568115709713366286068412036936894
42019-057257712923373816508438236620939095212258321427654942904356308649918402815387189841400777612703
52019-066660962242033550598055534764836369892245001571064232365157198344218115914836474381360207154477
62019-0764908328173340923896011395652396976121275412418048785948799910506116576816675073447350477660343
72019-0864404026980941056611514839925238794521873071357205203023336938524814176516379573440320877391624
82019-0961915523098333255810051927153333240731599431418814686933529958438115032316005066998325656496650
92019-106419591964593493978726521915825844311621451351075293113486178074916263515129668846366755754050
FechaDEDKESFIFRGBIENOSEITPLNLBEPTATTotal general
512023-04109537637533810016341571995739913278329174266278807862882890879357939265390164951210705799839767669
522023-0510193973353618062871353655707682430888153956217513734041797832299033247345163931192838710398175594
532023-069011013056229692681109025220861657232141086165259595626706786249611247189143838209990674116993007
542023-0769422335100613179791106075026301901092151578221598653206728463243194287296169281222847776047632604
552023-0874279832878911312941123904597211761828135672177556588706652420227225252639145244214956992407030478
562023-0965274826616411026751398043981321311398119185145249507581591130192316235825105614172574913716031766
572023-10493620284944117020699662373110106600411478614520674273061935019540718684296085154812904005833164
582023-11321133314893801272676322348369249497143320505894161942076313172712945465857101913655824798121
592023-1214549014412735256427345106752439866255397267936730117328860530638943713551137274142095061
60Total general40980827163569924230332956094232199741914453196082843929053073266945802851392584779579170615715506667661923412280379308030